Abstract:

The prediction of financial health in the commercial sector is a common matter compared to the non-profit sector. At present, scientists do not focus solely on commercial organizations, because non-profit organizations play an important role in several developed countries. Non-profit organizations usually perform tasks instead of private and public organizations. The article dealt with identification relevant variables which influence on financial vulnerability of non-profit organizations using binary logistic regression in IBM SPSS Statistics 25. The overall procedure consists of several parts, namely, to propose model, to qualify accuracy of prediction model and to validate model. The total sample consists of 351 Slovak non-profit organizations. Financial stability is estimated based on AGEORG, CONREV, CPTREV, DEBRAT, EQUREV, LOGASS, NCUASS, NWCASS, OPEMAR, PRAFOKOD, SALREV and TYPKOD. These variables are calculated based on the Financial Statements from the Ministry of Finance of the Slovak Republic (2018) and the Finstat (2018). The results show that OPEMAR, EQUREV, NWCASS, LOGASS and constant are part of logistic regression on backward principle. The article extends limited theoretical and empirical knowledge of non-profit organizations in the Slovak Republic. It should be emphasized that financial data on non-profit organizations are limited in compared to the commercial sector.